scholarly journals Transcriptomic Stratification of Late-Onset Alzheimer’s Cases Reveals Novel Genetic Modifiers of Disease Pathology

2019 ◽  
Author(s):  
Nikhil Milind ◽  
Christoph Preuss ◽  
Annat Haber ◽  
Guru Ananda ◽  
Shubhabrata Mukherjee ◽  
...  

ABSTRACTLate-Onset Alzheimer’s disease (LOAD) is a common, complex genetic disorder well-known for its heterogeneous pathology. The genetic heterogeneity underlying common complex diseases poses a major challenge for targeted therapies and the identification of novel disease-associated variants. Case-control approaches are often limited to examining a specific outcome in a group of heterogenous patients with different clinical characteristics. Here, we developed a novel approach to define relevant transcriptomic endophenotypes and stratify decedents based on molecular profiles in three independent human LOAD cohorts. By integrating post-mortem brain gene co-expression data from 2114 human samples with LOAD, we developed a novel quantitative, composite phenotype that can better account for the heterogeneity in genetic architecture underlying the disease. We used iterative weighted gene co-expression network analysis (WGCNA) analysis to reduce data dimensionality and to isolate gene sets that are highly co-expressed within disease subtypes and represent specific molecular pathways. We then performed single variant association testing using whole genome-sequencing data for the novel composite phenotype in order to identify genetic loci that contribute to disease heterogeneity. Distinct LOAD subtypes were identified for all three study cohorts (two in ROSMAP, three in Mayo Clinic, two in Mount Sinai Brain Bank). Single variant association analysis identified a genome-wide significant variant in TMEM106B (p-value < 5×10−8, rs1990620G) in the ROSMAP cohort that confers protection from the inflammatory LOAD subtype. Taken together, our novel approach can be used to stratify LOAD into distinct molecular subtypes based on affected disease pathways.

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Clémentine Escouflaire ◽  
Emmanuelle Rebours ◽  
Mathieu Charles ◽  
Sébastien Orellana ◽  
Margarita Cano ◽  
...  

Abstract Background In mammals, hypohidrotic ectodermal dysplasia (HED) is a genetic disorder that is characterized by sparse hair, tooth abnormalities, and defects in cutaneous glands. Only four genes, EDA, EDAR, EDARADD and WNT10A account for more than 90% of HED cases, and EDA, on chromosome X, is involved in 50% of the cases. In this study, we explored an isolated case of a female Holstein calf with symptoms similar to HED. Results Clinical examination confirmed the diagnosis. The affected female showed homogeneous hypotrichosis and oligodontia as previously observed in bovine EDAR homozygous and EDA hemizygous mutants. Under light microscopy, the hair follicles were thinner and located higher in the dermis of the frontal skin in the affected animal than in the control. Moreover, the affected animal showed a five-fold increase in the number of hair follicles and a four-fold decrease in the diameter of the pilary canals. Pedigree analysis revealed that the coefficient of inbreeding of the affected calf (4.58%) was not higher than the average population inbreeding coefficient (4.59%). This animal had ten ancestors in its paternal and maternal lineages. By estimating the number of affected cases that would be expected if any of these common ancestors carried a recessive mutation, we concluded that, if they existed, other cases of HED should have been reported in France, which is not the case. Therefore, we assumed that the causal mutation was dominant and de novo. By analyzing whole-genome sequencing data, we identified a large chromosomal inversion with breakpoints located in the first introns of the EDA and XIST genes. Genotyping by PCR-electrophoresis the case and its parents allowed us to demonstrate the de novo origin of this inversion. Finally, using various sources of information we present a body of evidence that supports the hypothesis that this mutation is responsible for a skewed inactivation of X, and that only the normal X can be inactivated. Conclusions In this article, we report a unique case of X-linked HED affected Holstein female calf with an assumed full inactivation of the normal X-chromosome, thus leading to a severe phenotype similar to that of hemizygous males.


2018 ◽  
Author(s):  
Laura J. Dunphy ◽  
Phillip Yen ◽  
Jason A. Papin

AbstractMetabolic adaptations accompanying the development of antibiotic resistance in bacteria remain poorly understood. To interrogate this relationship, we profiled the growth of lab-evolved antibiotic-resistant lineages of the opportunistic pathogenPseudomonas aeruginosaacross 190 unique carbon sources. We semi-automatically calculated growth dynamics (maximum growth density, growth rate, and time to mid-exponential phase) of over 2,800 growth curves. These data revealed that the evolution of antibiotic resistance resulted in systems-level changes to growth dynamics and metabolic phenotype. Drug-resistant lineages predominantly displayed decreased growth relative to the ancestral lineage; however, resistant lineages occasionally displayed enhanced growth on certain carbon sources, indicating that adaption to drug can provide a growth advantage in certain environments. A genome-scale metabolic network reconstruction (GENRE) ofP. aeruginosastrain UCBPP-PA14 was paired with whole-genome sequencing data of one of the drug-evolved lineages to predict genes contributing to observed changes in metabolism. Finally, we experimentally validatedin silicopredictions to identify genes mutated in resistantP. aeruginosaaffecting loss of catabolic function. Our results build upon previous mechanistic knowledge of drug-induced metabolic adaptation and provide a framework for the identification of metabolic limitations in antibiotic-resistant pathogens. Robust drug-driven changes in bacterial metabolism have the potential to be exploited to select against antibiotic-resistant populations in chronic infections.


2020 ◽  
Author(s):  
Alexander Smetanin ◽  
Nikita Moshkov ◽  
Tatiana V. Tatarinova

AbstractSummaryWe developed PyLAE - a new tool for determining local ancestry along a genome using whole-genome sequencing data or high-density genotyping experiments. PyLAE can process an arbitrarily large number of ancestral populations (with or without an informative prior). Since PyLAE does not involve estimation of many parameters, it can process thousands of genomes within a day. Computational efficiency, straightforward presentation of results, and an ease of installation makes PyLAE a useful tool to study admixed populations.Availability and implementationThe source code and installation manual are available at https://github.com/smetam/pylae.


2017 ◽  
Author(s):  
Adriana Munoz ◽  
Boris Yamrom ◽  
Yoon-ha Lee ◽  
Peter Andrews ◽  
Steven Marks ◽  
...  

AbstractCopy number profiling and whole-exome sequencing has allowed us to make remarkable progress in our understanding of the genetics of autism over the past ten years, but there are major aspects of the genetics that are unresolved. Through whole-genome sequencing, additional types of genetic variants can be observed. These variants are abundant and to know which are functional is challenging. We have analyzed whole-genome sequencing data from 510 of the Simons Simplex Collections quad families and focused our attention on intronic variants. Within the introns of 546 high-quality autism target genes, we identified 63 de novo indels in the affected and only 37 in the unaffected siblings. The difference of 26 events is significantly larger than expected (p-val = 0.01) and using reasonable extrapolation shows that de novo intronic indels can contribute to at least 10% of simplex autism. The significance increases if we restrict to the half of the autism targets that are intolerant to damaging variants in the normal human population, which half we expect to be even more enriched for autism genes. For these 273 targets we observe 43 and 20 events in affected and unaffected siblings, respectively (p-value of 0.005). There was no significant signal in the number of de novo intronic indels in any of the control sets of genes analyzed. We see no signal from de novo substitutions in the introns of target genes.


2020 ◽  
Author(s):  
Yingxi Yang ◽  
Yuchen Yang ◽  
Le Huang ◽  
Jai G. Broome ◽  
Adolfo Correa ◽  
...  

AbstractWith advances in whole genome sequencing (WGS) technology, multiple statistical methods for aggregate association testing have been developed. Many common approaches aggregate variants in a given genomic window of a fixed/varying size and are not reliant on existing knowledge to define appropriate test units, resulting in most identified regions not being clearly linked to genes, limiting biological understanding. Functional information from new technologies (such as Hi-C and its derivatives), which can help link enhancers to the genes they affect, can be leveraged to predefine variant sets for aggregate testing in WGS. Therefore, in this paper we propose the eSCAN (Scan the Enhancers) method for genome-wide assessment of enhancer regions in sequencing studies, combining the advantages of dynamic window selection in SCANG with the advantages of increased incorporation of genomic annotation. eSCAN searches biologically meaningful searching windows, increasing power and aiding biological interpretation, as demonstrated by simulation studies under a wide range of scenarios. We also apply eSCAN for association analysis of blood cell traits using TOPMed WGS data from Women’s Health Initiative (WHI) and Jackson Heart Study (JHS). Results from this real data example show that eSCAN is able to capture more significant signals, and these signals are of shorter length and drive association of larger regions detected by other methods.


BMC Genomics ◽  
2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Yu Wan ◽  
Ryan R. Wick ◽  
Justin Zobel ◽  
Danielle J. Ingle ◽  
Michael Inouye ◽  
...  

Abstract Background Horizontal gene transfer contributes to bacterial evolution through mobilising genes across various taxonomical boundaries. It is frequently mediated by mobile genetic elements (MGEs), which may capture, maintain, and rearrange mobile genes and co-mobilise them between bacteria, causing horizontal gene co-transfer (HGcoT). This physical linkage between mobile genes poses a great threat to public health as it facilitates dissemination and co-selection of clinically important genes amongst bacteria. Although rapid accumulation of bacterial whole-genome sequencing data since the 2000s enables study of HGcoT at the population level, results based on genetic co-occurrence counts and simple association tests are usually confounded by bacterial population structure when sampled bacteria belong to the same species, leading to spurious conclusions. Results We have developed a network approach to explore WGS data for evidence of intraspecies HGcoT and have implemented it in R package GeneMates (github.com/wanyuac/GeneMates). The package takes as input an allelic presence-absence matrix of interested genes and a matrix of core-genome single-nucleotide polymorphisms, performs association tests with linear mixed models controlled for population structure, produces a network of significantly associated alleles, and identifies clusters within the network as plausible co-transferred alleles. GeneMates users may choose to score consistency of allelic physical distances measured in genome assemblies using a novel approach we have developed and overlay scores to the network for further evidence of HGcoT. Validation studies of GeneMates on known acquired antimicrobial resistance genes in Escherichia coli and Salmonella Typhimurium show advantages of our network approach over simple association analysis: (1) distinguishing between allelic co-occurrence driven by HGcoT and that driven by clonal reproduction, (2) evaluating effects of population structure on allelic co-occurrence, and (3) direct links between allele clusters in the network and MGEs when physical distances are incorporated. Conclusion GeneMates offers an effective approach to detection of intraspecies HGcoT using WGS data.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Begoña Dobon ◽  
Rob ter Horst ◽  
Hafid Laayouni ◽  
Mayukh Mondal ◽  
Erica Bianco ◽  
...  

Abstract The Roma people are the largest transnational ethnic minority in Europe and can be considered the last human migration of South Asian origin into the continent. They left Northwest India approximately 1,000 years ago, reaching the Balkan Peninsula around the twelfth century and Romania in the fourteenth century. Here, we analyze whole-genome sequencing data of 40 Roma and 40 non-Roma individuals from Romania. We performed a genome-wide scan of selection comparing Roma, their local host population, and a Northwestern Indian population, to identify the selective pressures faced by the Roma mainly after they settled in Europe. We identify under recent selection several pathways implicated in immune responses, among them cellular metabolism pathways known to be rewired after immune stimulation. We validated the interaction between PIK3-mTOR-HIF-1α and cytokine response influenced by bacterial and fungal infections. Our results point to a significant role of these pathways for host defense against the most prevalent pathogens in Europe during the last millennium.


Genes ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 631
Author(s):  
Maria Pina Concas ◽  
Massimiliano Cocca ◽  
Margherita Francescatto ◽  
Thomas Battistuzzi ◽  
Beatrice Spedicati ◽  
...  

To date, little is known about the role of olfactory receptor (OR) genes on smell performance. Thanks to the availability of whole-genome sequencing data of 802 samples, we identified 41 knockout (KO) OR genes (i.e., carriers of Loss of Function variants) and evaluated their effect on odor discrimination in 218 Italian individuals through recursive partitioning analysis. Furthermore, we checked the expression of these genes in human and mouse tissues using publicly available data and the presence of organ-related diseases in human KO (HKO) individuals for OR expressed in non-olfactory tissues (Fisher test). The recursive partitioning analysis showed that age and the high number (burden) of OR-KO genes impact the worsening of odor discrimination (p-value < 0.05). Human expression data showed that 33/41 OR genes are expressed in the olfactory system (OS) and 27 in other tissues. Sixty putative mouse homologs of the 41 humans ORs have been identified, 58 of which are expressed in the OS and 37 in other tissues. No association between OR-KO individuals and pathologies has been detected. In conclusion, our work highlights the role of the burden of OR-KO genes in worse odor discrimination.


2021 ◽  
Author(s):  
Hanna Sigeman ◽  
Bella Sinclair ◽  
Bengt Hansson

Sex chromosomes have evolved numerous times, as revealed by recent genomic studies. However, large gaps in our knowledge of sex chromosome diversity across the tree of life remain. Filling these gaps, through the study of novel species, is crucial for improved understanding of why and how sex chromosomes evolve. Characterization of sex chromosomes in already well-studied organisms is also important to avoid misinterpretations of population genomic patterns caused by undetected sex chromosome variation. Here we present findZX, an automated Snakemake-based computational pipeline for detecting and visualizing sex chromosomes through differences in genome coverage and heterozygosity between males and females. FindZX is user-friendly and scalable to suit different computational platforms and works with any number of male and female samples. An option to perform a genome coordinate lift-over to a reference genome of another species allows users to inspect sex- linked regions over larger contiguous chromosome regions, while also providing important between- species synteny information. To demonstrate its effectiveness, we applied findZX to publicly available genomic data from species belonging to widely different taxonomic groups (mammals, birds, reptiles, fish, and insects), with sex chromosome systems of different ages, sizes, and levels of differentiation. We also demonstrate that the lift-over method is robust over large phylogenetic distances (>80 million years of evolution).


PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12502
Author(s):  
Nikita Moshkov ◽  
Aleksandr Smetanin ◽  
Tatiana V. Tatarinova

Summary We developed PyLAE, a new tool for determining local ancestry along a genome using whole-genome sequencing data or high-density genotyping experiments. PyLAE can process an arbitrarily large number of ancestral populations (with or without an informative prior). Since PyLAE does not involve estimating many parameters, it can process thousands of genomes within a day. PyLAE can run on phased or unphased genomic data. We have shown how PyLAE can be applied to the identification of differentially enriched pathways between populations. The local ancestry approach results in higher enrichment scores compared to whole-genome approaches. We benchmarked PyLAE using the 1000 Genomes dataset, comparing the aggregated predictions with the global admixture results and the current gold standard program RFMix. Computational efficiency, minimal requirements for data pre-processing, straightforward presentation of results, and ease of installation make PyLAE a valuable tool to study admixed populations. Availability and implementation The source code and installation manual are available at https://github.com/smetam/pylae.


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